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This paper proposes obtaining maximum and minimum daily cumulative energy curves and introduces novel hourly and daily energy flexibility indices. Also, it develops a generic methodology that quantifies and formulates energy flexibility as the possible power increase (P&#x005F;in) or decrease (P&#x005F;dec) within operational limits. The proposed method can be applied to derive maximum and minimum energy flexibility curves for different devices and aggregate them to extract hourly or daily energy flexibility indices based on the calculation area between daily cumulative energy curves in an hour and 24 hours. The proposed energy flexibility estimation is evaluated by doing offline digital time-domain simulations on a 100-bus home-residential active distribution network (ADN), including flexible equipment/devices (e.g., washing machines, dishwashers, domestic heat water, battery, photovoltaic (PV) panels, and plug-in hybrid electric vehicle (PHEV) charging stations) in MATLAB/Simulink software environment. Then, a price-sensitive model of every flexible equipment is introduced, and ultimately, the effect of electricity price changes on energy flexibility is evaluated. The simulations and comparisons of the energy flexibility potential of different pricing scenarios effectively prove the proposed strategy&#x2019;s effectiveness, accuracy, and authenticity.

Aggregator Index for 24-hour Energy Flexibility Evaluation in an ADN including PHEVs